In many fields (e.g. Internet of Things, IoT, smart homes, or Wireless Sensor Networks, WSN), location-awareness for embedded devices is desired or even crucial. Such small electronic devices, however, are usually unable to determine their own location due to restrictions in size, cost, and/or power consumption. Conventional location-determination (also referred to herein as positioning and localization) techniques using Radio Frequency (RF) signals, audio signals, or magnetic signals are severely limited in accuracy, range, or both.
Further, the complexity of 3D motion tracking and indoor positioning is problematic. Devices in the fields of industrial automation, autonomous robotics, augmented reality (AR), and virtual reality (VR) currently rely on complex systems, such as described above, for positioning. This hinders the development of ubiquitous location-aware devices. Conventional systems, e.g., use combinations of ToF sensors, wide-angle motion tracking cameras, inertial sensors and a dedicated computer vision processor. This results in complex systems with excessive cost, size, and/or power consumption. Similarly, the association of stationary electronic devices with geometric positions is problematic. Even if the expected positions are known, it can be labor-intensive to manually determine which device is located at which position.
New approaches involving image-sensor-based localization and tracking systems have been proposed. These systems can be sufficiently accurate to determine the position and orientation of electronic devices. More specifically, these systems often use Time-of-Flight (ToF) three-dimensional sensors in combination with small reflective markers (also referred to as “tags” or “devices”). Such systems can determine the position and orientation of a device at a rate of several hundred times per second (Hz).
Even though such systems provide accurate localization, the simplicity of reflective tags severely limits the possibility of further interaction, which is important for many of the applications mentioned above. For example, interaction is especially important for AR/VR applications. In other words, such systems generally require another transmission system (e.g., an RF communication system, such as Bluetooth) between the device the sensor to facilitate the information transfer needed for interaction. Much like the positioning systems described above, these systems can introduce unwanted complexity, cost, size, and/or power consumption.